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Aug 11, 2023
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2 changes: 1 addition & 1 deletion doc/python/animations.md
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Expand Up @@ -37,7 +37,7 @@ jupyter:

Several [Plotly Express](/python/plotly-express/) functions support the creation of animated figures through the `animation_frame` and `animation_group` arguments.

Here is an example of an animated scatter plot creating using Plotly Express. Note that you should always fix the `x_range` and `y_range` to ensure that your data remains visible throughout the animation.
Here is an example of an animated scatter plot created with Plotly Express. Note that you should always fix the `x_range` and `y_range` to ensure that your data remains visible throughout the animation.

```python
import plotly.express as px
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2 changes: 1 addition & 1 deletion doc/python/interactive-html-export.md
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Expand Up @@ -46,7 +46,7 @@ Any figure can be saved as an HTML file using the `write_html` method. These HTM
```python
import plotly.express as px

fig =px.scatter(x=range(10), y=range(10))
fig = px.scatter(x=range(10), y=range(10))
fig.write_html("path/to/file.html")
```
<!-- #endregion -->
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2 changes: 1 addition & 1 deletion doc/python/px-arguments.md
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Expand Up @@ -35,7 +35,7 @@ jupyter:

### Plotly Express works with Column-oriented, Matrix or Geographic Data

[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces [easy-to-style figures](/python/styling-plotly-express/).
[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).

Plotly Express provides functions to visualize a variety of types of data. Most functions such as `px.bar` or `px.scatter` expect to operate on column-oriented data of the type you might store in a `DataFrame` (in either "long" or "wide" format, see below). These functions use Pandas internally to process the data, but also accept other types of DataFrames as arguments. See the **Input Data as Non-Pandas DataFrames** section below for more details.

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